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Ship detection aims to automatically identify whether there are ships in the images, precisely classifies and localizes them. Regardless of whether utilizing early manually designed methods or deep learning technology, ship detection is dedicated to exploring the inherent characteristics of ships to enhance recall. Nowadays, high-precision ship detection plays a crucial role in civilian and military applications. In order to provide a comprehensive review of ship detection in optical remote-sensing images (SDORSIs), this paper summarizes the challenges as a guide. These challenges include complex marine environments, insufficient discriminative features, large scale variations, dense and rotated distributions, large aspect ratios, and imbalances between positive and negative samples. We meticulously review the improvement methods and conduct a detailed analysis of the strengths and weaknesses of these methods. We compile ship information from common optical remote sensing image datasets and compare algorithm performance. Simultaneously, we compare and analyze the feature extraction capabilities of backbones based on CNNs and Transformer, seeking new directions for the development in SDORSIs. Promising prospects are provided to facilitate further research in the future. [ABSTRACT FROM AUTHOR]

Similar to silicon-based electronics, the implementation of micro/nano-patterning to facilitate complex device architectures and high-density integration is crucial to the development of organic electronics. Among various patterning techniques, direct microlithography (DML) is highly applicable and extensively adopted in organic electronics, such as organic electrochemical transistors (OECTs). However, conventional DML often requires high crosslinker concentrations, leading to compromised electrical performance. To address this challenge, a novel strategy is developed that combines supramolecular and covalent interactions by incorporating a polyrotaxane supramolecular crosslinker (PR) into poly(benzodifurandione) (PBFDO). The PR forms a hydrogen bonding network with PBFDO and undergoes UV-triggered covalent crosslinking among its molecules, providing solvent resistance even at trace loading levels (<0.1 wt%). This approach enables precise patterning of PBFDO with feature sizes below 1 µm while preserving high electrical performance. Notably, PR also serves as a performance enhancer, promoting molecular ordering and ionic conduction within PBFDO. OECTs fabricated with PR-crosslinked PBFDO exhibit about one-order-of-magnitude increase in ON/OFF ratio, a 42% increase in µC * (reaching 2460 F cm -1  V -1  s -1 ), and elevated operational stability compared to pristine ones. This multifunctional crosslinker offers a scalable solution for high-performance, high-density organic electronics and opens new avenues for supramolecular chemistry applications in this field., (© 2025 Wiley‐VCH GmbH.)

Background: Creatine is essential for energy storage and transfer within and outside cells. However, its relationship with cerebrovascular disease has not been fully explored. This study examined the association between serum creatine levels and postoperative cerebrovascular events, including transient ischemic attack (TIA), ischemic stroke, and hemorrhagic stroke, in patients with moyamoya disease (MMD)., Methods: Serum creatine and disodium creatine phosphate levels were quantified in 352 patients with MMD using liquid chromatography-tandem mass spectrometry. Kaplan-Meier (KM) curves were used to analyze the impact of serum creatine levels on cerebrovascular event risk, whereas univariate and multivariate Cox regression analyses were used to identify predictors of postoperative outcomes. A prognostic nomogram was developed to predict stroke-free survival at 12, 24, and 36 months postoperatively., Results: In patients with MMD, serum creatine showed a negative correlation with creatinine (r = -0.22; p < 0.001) and homocysteine (r = -0.10; p < 0.05) but not with disodium creatine phosphate (r = -0.08; p = 0.15). When patients were divided into high and low groups based on the median serum creatine concentration, KM curve analysis revealed that patients in the high concentration group had a lower relative risk of cerebrovascular events than those in the low concentration group (hazard ratio: 0.55; 95% confidence interval, 0.33-0.94; p = 0.026). Furthermore, when patients were categorized into three levels based on creatine concentration, the overall KM curve analysis showed a significant difference (p = 0.038), such that the highest creatine concentration group (third tertile) showed a significantly reduced risk compared with the lowest concentration group (first tertile; p = 0.04)., Conclusion: Lower preoperative serum creatine levels were associated with a higher risk of postoperative cerebrovascular events in patients with MMD. Therefore, creatine supplementation may be an effective means of preventing adverse outcomes in patients with MMD., (© 2025 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

Growing evidence suggests that systemic immune and inflammatory responses may play a critical role in the formation and development of aneurysms. Exploring the differences between single intracranial aneurysm (SIA) and multiple IAs (MIAs) could provide insights for targeted therapies. However, there is a lack of comprehensive and detailed characterization of changes in circulating immune cells in MIAs. Peripheral blood mononuclear cell (PBMC) samples from patients with SIA (n = 16) or MIAs (n = 6) were analyzed using high-dimensional mass cytometry to evaluate the frequency and phenotype of immune cell subtypes. A total of 25 cell clusters were identified, revealing that the immune signature of MIAs included cluster changes. Compared to patients with SIA, patients with MIAs exhibited immune dysfunction and regulatory imbalance in T-cell clusters. They also had reduced numbers of CD8+ T cells and their subgroups CD8+ Te and CD8+ Tem cells, as well as reduced numbers of the CD4+ T-cell subgroup CD27-CD4+ Tem cells. Furthermore, compared to SIA, MIAs were associated with enhanced T-cell immune activation, with elevated expression levels of CD3, CD25, CD27, CCR7, GP130, and interleukin 10. This study provides insights into the circulating immune cell profiles in patients with MIAs, highlighting the similarities and differences between patients with SIA and those with MIAs. Furthermore, the study suggests that circulating immune dysfunction may contribute to the development of MIAs., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Immunology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objective: To develop and evaluate a nomogram prediction model for the 3-month mortality risk of patients with sepsis-associated acute kidney injury (S-AKI)., Methods: Based on the American Medical Information Mart for Intensive Care- IV (MIMIC- IV), clinical data of S-AKI patients from 2008 to 2021 were collected. Initially, 58 relevant predictive factors were included, with all-cause mortality within 3 months as the outcome event. The data were divided into training and testing sets at a 7 : 3 ratio. In the training set, univariate Logistic regression analysis was used for preliminary variable screening. Multicollinearity analysis, Lasso regression, and random forest algorithm were employed for variable selection, combined with the clinical application value of variables, to establish a multivariable Logistic regression model, visualized using a nomogram. In the testing set, the predictive value of the model was evaluated through internal validation. The receiver operator characteristic curve (ROC curve) was drawn, and the area under the curve (AUC) was calculated to evaluate the discrimination of nomogram model and Oxford acute severity of illness score (OASIS), sequential organ failure assessment (SOFA), and systemic inflammatory response syndrome score (SIRS). The calibration curve was used to evaluate the calibration, and decision curve analysis (DCA) was performed to assess the net benefit at different probability thresholds., Results: Based on the survival status at 3 months after diagnosis, patients were divided into 7 768 (68.54%) survivors and 3 566 (31.46%) death. In the training set, after multiple screenings, 7 variables were finally included in the nomogram model: Logistic organ dysfunction system (LODS), Charlson comorbidity index, urine output, international normalized ratio (INR), respiratory support mode, blood urea nitrogen, and age. Internal validation in the testing set showed that the AUC of nomogram model was 0.81 [95% confidence interval (95%CI) was 0.80-0.82], higher than the OASIS score's 0.70 (95%CI was 0.69-0.71) and significantly higher than the SOFA score's 0.57 (95%CI was 0.56-0.58) and SIRS score's 0.56 (95%CI was 0.55-0.57), indicating good discrimination. The calibration curve demonstrated that the nomogram model's calibration was better than the OASIS, SOFA, and SIRS scores. The DCA curve suggested that the nomogram model's clinical net benefit was better than the OASIS, SOFA, and SIRS scores at different probability thresholds., Conclusions: A nomogram prediction model for the 3-month mortality risk of S-AKI patients, based on clinical big data from MIMIC- IV and including seven variables, demonstrates good discriminative ability and calibration, providing an effective new tool for assessing the prognosis of S-AKI patients.